Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: February 28, 2008
Publication Date: June 28, 2008
Citation: Sheen,S.2008.Modeling surface transfers of Listeria Monocytogenes between salami and round blade [abstract].IFT Annual Meeting.New Orleans,LA.p.1. Technical Abstract: Several listeriosis outbreaks linked to the consumption of pre-sliced ready-to-eat (RTE) deli meats have drawn increased attention with regard to the possible cross-contamination of Listeria monocytogenes (Lm) during the slicing operations in retail food service establishment. The objective of this study was to investigate the surface transfer of Lm between a meat slicer and salami slices (15% fat) and to understand the potential impact on food safety. To simulate the slicing process (with a 300 mm-diameter round blade), a six-strain Lm cocktail was inoculated onto a slicer blade to an initial level of ca. 3, 5, 6, 7 or 9 log CFU/blade (or ca. 2, 4, 5, 6 or 8 log CFU/cm-squared of the blade edge area), and then the salami was sliced to a thickness of 1-2 mm. Another cross-contamination simulation, a clean blade was used to slice previously inoculated salami with Lm (ca. 3, 5, 6, 7, 8 or 9 log CFU on 100 cm-squared of salami surface) followed by slicing of salami that was not inoculated. The salami slicing speed was maintained at a constant average rate 3-4 slices/minute. The empirical models, developed using the TableCurve2D (SYSTAT Software Inc.), predicted the trend/pattern of Lm transfer well between the blade and salami slices for contamination level of 5 log CFU and higher. With 3 or 4 log CFU level, the experimental transfer showed random Lm on sliced salami and no model may be developed to represent the data. The currently reported non-linear models are microbial load (n), sequential slice number (X), and contamination route dependent. The models may be applied to predict the Lm transfer trends in relatively low Lm level (4 log CFU and below) cross-contamination of salami slicing process and will serve as a building block in microbial risk assessment.